Tokyo · AI Readiness Audit
Is your Tokyo hotel found when customers ask AI?
When someone in Tokyo asks ChatGPT “boutique hotel near Shinjuku station with 24-hour check-in”, does your hotel come up — or your competitor? A $47 audit shows exactly what AI assistants can and can't see about your business, and how to fix it.
What stops most Tokyo hotels from being found by AI
Most hotel websites were built before AI-assistant discovery existed. These are the gaps we see most often — and exactly what the audit scores:
- ✗Room types, amenities, and check-in policy aren't in Schema.org
- ✗AI sends travelers to Booking.com instead of your direct-booking page
- ✗No geo coordinates at the precision AI needs for "near [landmark]" queries
- ✗No entity disambiguation (sameAs / Wikidata) in a city full of similar names
What the $47 audit delivers
AI-readiness score (0-100)
How visible your hotel is to ChatGPT, Claude, Gemini, and Perplexity today.
The specific gaps
Which Schema.org fields, robots.txt rules, and llms.txt entries you're missing — for a Japan hotel.
Concrete next steps
A prioritized fix list you can hand to any developer — or have us build.
Local context
How Tokyo's platforms (Tabelog, Hot Pepper Beauty) and Japanese-first mix affect your discoverability.
Tokyo Hotel & Lodging AI-readiness — FAQ
How do Tokyo customers find a hotel using AI assistants?
Increasingly, Tokyo customers ask ChatGPT, Claude, Gemini, or Perplexity questions like "boutique hotel near Shinjuku station with 24-hour check-in" instead of scrolling Tabelog or Google. The AI returns a short list of specific businesses. If your hotel isn't structured for AI to read — no Schema.org, no llms.txt, content locked in JavaScript — you're invisible in that answer regardless of how good your business is.
What does the $47 audit check for a Tokyo hotel?
It scores your site 0-100 on AI-readiness: robots.txt rules for AI crawlers (OAI-SearchBot, Claude-SearchBot, PerplexityBot), Schema.org structured data, llms.txt presence, server-side rendering, and the content patterns proven to lift AI citation. The report is specific to your hotel and the Japan market — including which local platforms (Tabelog, Hot Pepper Beauty, Google Maps, LINE Official Account) you're over-reliant on.
Why does the Japan market matter for AI-readiness?
Tokyo is Japanese-first, with a high-value English-speaking expat and tourist segment. AI assistants weigh language signals, local entity data, and market-specific platforms differently here than elsewhere. A generic audit misses this; ours accounts for Tokyo-specific discovery (Tabelog and Hot Pepper Beauty) and the bilingual surface that wins higher-value segments.
Want the full playbook? Read our deep-dive on how hotels get cited by AI →
See where your Tokyo hotel stands.
$47. 24-48 hours. 30-day money-back guarantee.
Get Your $47 Audit →